A novel method for identifying fine-scale bottom-use in a benthic-foraging pinniped.

Area of Science:

• Marine biology
• Animal movement ecology
• Conservation technology

Background:

• Accelerometer and magnetometer data offer insights into sub-surface foraging behaviors of marine predators, complementing traditional location and time-depth data.
• These sensors measure head movement and body orientation, aiding in the identification of foraging shifts, habitat utilization, and energy expenditure in various species.
• Australian sea lions, an endangered species, require identification of critical foraging areas for effective population management.

Purpose of the Study:

• To develop and apply a novel method using accelerometer and magnetometer data to identify key benthic foraging areas for Australian sea lions.
• To provide a fine-scale analysis of underwater movement and habitat use beyond what GPS and dive data alone can offer.

Main Methods:

• Utilized tri-axial magnetometer and accelerometer data from tagged Australian sea lions, combined with GPS and dive data, to reconstruct 3D foraging paths.
• Isolated benthic phases of foraging trips and calculated dive metrics to characterize bottom usage.
• Employed k-means cluster analysis to identify core benthic areas and stepwise regressions to model bottom usage predictors.

Main Results:

• Demonstrated distinct spatial partitioning in benthic habitat use among Australian sea lions.
• Identified individual variations in benthic habitat utilization patterns.
• Revealed tortuous foraging movements employed by Australian sea lions to exploit key benthic marine habitats and features using high-resolution sensor data.

Conclusions:

• Magnetometer and accelerometer data provide a detailed description of underwater movement for diving species, enhancing traditional tracking methods.
• The developed method aids in identifying critical foraging areas for endangered species like the Australian sea lion, supporting spatially targeted conservation efforts.
• This approach can be applied to both marine and terrestrial species, with potential for further augmentation by integrating habitat and prey data.